Introducing eBird/Macaulay Library Media Search!

Black-bellied Plover by Ian Davies

We are excited to release eBird/Macaulay Library Media Search, a tool for exploring photos and sounds uploaded through eBird, as well as the full collection of bird sounds and video archived in the Macaulay Library through traditional methods. With more than half a million images and thousands of audio files uploaded to eBird over the past five months there is plenty to explore! This initial version of Media Search is focused on providing results for species, date range, and location combinations, while subsequent development will focus on increasing the metadata associated with uploaded media, and building out advanced search capabilities. We hope these tools provide an exciting environment to explore the contributions of others, and also to increase the public visibility of your own efforts. Take the new Media Search tool for a test drive right now!

This integrated functionality is a great example of the close connection developing between eBird and the Macaulay Library at the Cornell Lab, as each piece of rich media that you upload to eBird automatically becomes a digital specimen archived in the Macaulay Library. This collaboration will help us continue to build a global collection of rich media in the Macaulay Library, while also supporting the millions of bird observations reported from eBird around the world—giving researchers and birders tools to make these photos, sounds, and videos easily accessible and searchable. From a birder’s perspective, this new Media Search provides an excellent growing resource for identification material, as well as a means to answer countless questions about birds. The possibilities from a research standpoint are vast as well, as each record submitted to eBird can now be supported with evidence in the form of photos and sounds.

The release of Media Search marks another important day in eBird’s history: the advent of community review. For more than a decade, eBird has built its data quality process on a combination of automated data processing by computers and human intelligence; leveraging the strengths of both to create the most comprehensive data quality system available in a citizen-science project. Today that process is evolving, moving in the direction of harnessing the power of our community to help vet the millions of bird records now coming in to eBird each month. As a first step in community review, a subset of the eBird community will be able to flag photos and sounds as misidentified. In order to test this community review process, we are extending this functionality first to eBirders who have submitted at least 365 eBird checklists in the past year (2015). We will evaluate how this process is working, and make a decision as to how to get more people involved moving forward. Thank you to everyone who submitted 365 checklists last year, and we hope to see more people meet that threshold in 2016! Even if you’ve only submitted one checklist to eBird, thank you for your help in making eBird the best it can be. Enjoy the new Media Search!